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[None][test] Unwaive DeepSeekV3.2 nvfp4 mtp3_fp8kv_chunked test - #15973

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NVIDIA:mainfrom
yizhang-nv:codex/fix-one-engine-spec-scheduler-budget
Aug 11, 2026
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[None][test] Unwaive DeepSeekV3.2 nvfp4 mtp3_fp8kv_chunked test#15973
yizhang-nv merged 1 commit into
NVIDIA:mainfrom
yizhang-nv:codex/fix-one-engine-spec-scheduler-budget

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@yizhang-nv yizhang-nv commented Jul 6, 2026

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Description

Unwaives accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_piecewise_cuda_graph[mtp3_fp8kv_chunked] (NVBug 5989920).

Two separate defects kept this test failing; both are fixed elsewhere:

  1. Scheduler token budgettotal_num_tokens (8195) should be <= max_num_tokens (8192) under one-model MTP with chunked prefill + overlap scheduler. Fixed on main by [https://nvbugs/6427240][fix] Reserve MTP draft tokens in scheduler for one-model speculative decoding #16101.
  2. Stale CUDA graph pool — with torch.compile enabled, Backend._graph_pool_handle is class state shared by every engine in the process. Engine teardown resets the graphs captured into that pool, dropping its use_count to zero, but the caching allocator only erases the entry once the pool has no blocks left. The next engine in the same worker process then captured into the retired handle and hit it->second->use_count > 0 INTERNAL ASSERT FAILED in beginAllocateToPool. Fixed by [https://nvbugs/6475346][fix] Avoid stale CUD… #16952, which removes the shared class handle entirely and lets each capture create its own private pool.

This PR depends on #16952 landing first. Verified on 8x B200 that with that class of fix applied, running [baseline] and [mtp3_fp8kv_chunked] back to back in one pytest session goes from 1 failed, 1 passed to 2 passed. Without it the test still fails, because the CI stage runs [baseline] first and the MPI workers are reused across both — which is also why the test passes when run standalone.

Test Coverage

accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_piecewise_cuda_graph[mtp3_fp8kv_chunked], re-enabled by this PR, runs in DGX_B200-8_GPUs-PyTorch-*.

Post-fix accuracy measured on 8x B200: MMLU 87.865 (reference 87.200), GSM8K 95.072 (reference 95.600).

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@yizhang-nv
yizhang-nv requested a review from a team as a code owner July 6, 2026 09:51
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Walkthrough

The backend now creates a fresh CUDA graph pool handle after graph teardown. Model engine cleanup invokes this rotation after clearing graph runners. One waived DeepSeek integration test entry was removed.

Changes

CUDA graph pool lifecycle

Layer / File(s) Summary
Rotate the shared graph pool during teardown
tensorrt_llm/_torch/compilation/backend.py, tensorrt_llm/_torch/pyexecutor/model_engine.py
Backend.rotate_graph_pool_handle() creates a new CUDA graph pool handle. _release_cuda_graphs invokes it after clearing captured graphs.
Remove the resolved test waiver
tests/integration/test_lists/waives.txt
The waiver for TestDeepSeekV32::test_nvfp4_multi_gpus_piecewise_cuda_graph[mtp3_fp8kv_chunked] was removed.

Estimated code review effort: 2 (Simple) | ~10 minutes

Possibly related PRs

Suggested reviewers: schetlur-nv, mlefeb01, qijune

🚥 Pre-merge checks | ✅ 5
✅ Passed checks (5 passed)
Check name Status Explanation
Docstring Coverage ✅ Passed No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
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Title check ✅ Passed The title clearly identifies the test change and follows the required ticket and type format.
Description check ✅ Passed The description explains the issue, dependent fixes, test coverage, results, and checklist status in sufficient detail.
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chungen28 added a commit to deepinfra/TensorRT-LLM that referenced this pull request Jul 24, 2026
…upstream PR NVIDIA#15973)

Squash of upstream PR NVIDIA#15973 (4 commits). One-engine speculative
decoders (MTP / DSpark) keep the draft model inside ModelEngine, so PyExecutor.drafter
is None; under the overlap scheduler the next draft tokens are produced by the previous
batch and their count may not be copied to the C++ request before the next scheduling
pass, so the scheduler can budget a gen request as 1 token though the model consumes
1+K -> oversized mixed context/generation batch (total_num_tokens > max_num_tokens).

Run scheduler-facing draft-token reservation for every speculative decoder immediately
before scheduling (_prepare_scheduler_draft_tokens); placeholder token values are not
consumed, their length reserves the correct micro-batch capacity. Includes: skip when
spec decode is disabled, handle lightweight executor fixtures, and unwaive the
DeepSeekV3 nvfp4 mtp3_fp8kv_chunked test that exposed the bug.

Signed-off-by: chungen28 <chung-en@deepinfra.com>
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yizhang-nv force-pushed the codex/fix-one-engine-spec-scheduler-budget branch from b71f9f0 to 1639857 Compare August 5, 2026 06:38
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@yizhang-nv yizhang-nv changed the title [None][fix] Reserve one-engine speculative tokens before scheduling [None][test] Unwaive DeepSeekV3.2 nvfp4 mtp3_fp8kv_chunked test Aug 5, 2026
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/bot run --disable-fail-fast --stage-list "DGX_B200-8_GPUs-PyTorch-1, DGX_B200-8_GPUs-PyTorch-2, DGX_B200-8_GPUs-PyTorch-3, DGX_B200-8_GPUs-PyTorch-4"

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PR_Github #64174 [ run ] triggered by Bot. Commit: 4faea3e Link to invocation

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PR_Github #64174 [ run ] completed with state FAILURE. Commit: 4faea3e
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yizhang-nv force-pushed the codex/fix-one-engine-spec-scheduler-budget branch from 4faea3e to fdebd71 Compare August 6, 2026 07:58
@yizhang-nv yizhang-nv changed the title [None][fix] Retire the shared CUDA graph pool handle on engine teardown [None][test] Unwaive DeepSeekV3.2 nvfp4 mtp3_fp8kv_chunked test Aug 6, 2026
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Unwaive TestDeepSeekV32::test_nvfp4_multi_gpus_piecewise_cuda_graph[mtp3_fp8kv_chunked]
(nvbugs/5989920) to re-enable it in CI.

Signed-off-by: Yi Zhang <187001205+yizhang-nv@users.noreply.github.com>
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yizhang-nv merged commit 26842d1 into NVIDIA:main Aug 11, 2026
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